SparseDC: Implementation of SparseDC Algorithm

Implements the algorithm described in Barron, M., Zhang, S. and Li, J. 2017, "A sparse differential clustering algorithm for tracing cell type changes via single-cell RNA-sequencing data", Nucleic Acids Research, gkx1113, <doi:10.1093/nar/gkx1113>. This algorithm clusters samples from two different populations, links the clusters across the conditions and identifies marker genes for these changes. The package was designed for scRNA-Seq data but is also applicable to many other data types, just replace cells with samples and genes with variables. The package also contains functions for estimating the parameters for SparseDC as outlined in the paper. We recommend that users further select their marker genes using the magnitude of the cluster centers.

Version:	0.1.17
Depends:	R (≥ 3.1.0)
Imports:	stats
Suggests:	knitr, rmarkdown
Published:	2018-01-04
DOI:	10.32614/CRAN.package.SparseDC
Author:	Jun Li [aut, cre], Martin Barron [aut]
Maintainer:	Jun Li <jun.li at nd.edu>
License:	GPL-3
NeedsCompilation:	no
CRAN checks:	SparseDC results

Documentation:

Reference manual:	SparseDC.pdf
Vignettes:	sparseDC

Downloads:

Package source:	SparseDC_0.1.17.tar.gz
Windows binaries:	r-devel: SparseDC_0.1.17.zip, r-release: SparseDC_0.1.17.zip, r-oldrel: SparseDC_0.1.17.zip
macOS binaries:	r-release (arm64): SparseDC_0.1.17.tgz, r-oldrel (arm64): SparseDC_0.1.17.tgz, r-release (x86_64): SparseDC_0.1.17.tgz, r-oldrel (x86_64): SparseDC_0.1.17.tgz
Old sources:	SparseDC archive

Reverse dependencies:

Reverse suggests:

splatter

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